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# Apache License, Version 2.0 (the "License"); you may not use this file except in
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#
#     http://www.apache.org/licenses/LICENSE-2.0
#
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"""Module houses default Rolling functions builder class."""

from .default import DefaultMethod


# FIXME: there is no sence of keeping `Rolling` and `RollingDefault` logic in a different
# classes. They should be combined.
class Rolling:
    """Builder for aggregation on a rolling window functions."""

    @classmethod
    def build_rolling(cls, func):
        """
        Build function that creates a rolling window and executes `func` on it.

        Parameters
        ----------
        func : callable
            Function to execute on a rolling window.

        Returns
        -------
        callable
            Function that takes pandas DataFrame and applies `func` on a rolling window.
        """

        def fn(df, rolling_args, *args, **kwargs):
            """Create rolling window for the passed frame and execute specified `func` on it."""
            rolling_args, rolling_kw = rolling_args
            roller = df.rolling(*rolling_args, **rolling_kw)

            if type(func) == property:
                return func.fget(roller)

            return func(roller, *args, **kwargs)

        return fn


class RollingDefault(DefaultMethod):
    """Builder for default-to-pandas aggregation on a rolling window functions."""

    OBJECT_TYPE = "Rolling"

    @classmethod
    def register(cls, func, **kwargs):
        """
        Build function that do fallback to pandas to apply `func` on a rolling window.

        Parameters
        ----------
        func : callable
            Function to execute on a rolling window.
        **kwargs : kwargs
            Additional arguments that will be passed to function builder.

        Returns
        -------
        callable
            Function that takes query compiler and defaults to pandas to apply aggregation
            `func` on a rolling window.
        """
        return super().register(
            Rolling.build_rolling(func), fn_name=func.__name__, **kwargs
        )
